Neuroimmunological antibody-mediated encephalitis and implications for diagnosis and therapy in neuropsychiatry
Bibliographic record
Abstract
The past decade has seen a surge of reports and investigations into cases of autoimmune-mediated encephalitis. The increasing recognition of these disorders is especially of relevance to the fields of neurology and psychiatry. Autoimmune encephalitis involves antibodies against synaptic receptors, neuronal cell surface proteins and intracellular targets. These disorders feature prominent symptoms of cognitive impairment and behavioural changes, often associated with the presence of seizures. Early in the clinical course, autoimmune encephalitis may manifest as psychiatric symptoms of psychosis and involve psychiatry as an initial point of contact. Although commonly associated with malignancy, these disorders can present in the absence of an inciting neoplasm. The identification of autoimmune encephalitis is of clinical importance as a large proportion of individuals experience a response to immunotherapy. This review focuses on the current state of knowledge on n-methyl-d-aspartate (NMDA) receptor-associated encephalitis and limbic encephalitis, the latter predominantly involving antibodies against the α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptor, the γ-aminobutyric acid (GABA)B receptor and leucine-rich glioma-inactivated 1 (LGI1) protein. In addition, we briefly describe anti-dopamine D2 receptor encephalitis. A summary of the literature will focus on common clinical presentations and course, diagnostic approaches and response to treatment. Since a substantial proportion of patients with autoimmune encephalitis exhibit symptoms of psychosis, the relevance of this disorder to theories of psychosis and schizophrenia will also be discussed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".